README.md

---
language:
- en
license: apache-2.0
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- tobiolatunji/afrispeech-200
metrics:
- wer
model-index:
- name: Whisper Small En - Moh
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: AfriSpeech
      type: tobiolatunji/afrispeech-200
      config: all
      split: train
      args: 'config: en, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 32.87142507484043
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# Whisper Small En - Moh

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the AfriSpeech dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6236
- Wer: 32.8714

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.677         | 0.5   | 500  | 0.6841          | 31.2466 |
| 0.428         | 1.0   | 1000 | 0.6236          | 32.8714 |


### Framework versions

- Transformers 4.27.0.dev0
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2